Conferences related to Discrete Cosine Transform

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


IECON 2020 - 46th Annual Conference of the IEEE Industrial Electronics Society

IECON is focusing on industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.


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Periodicals related to Discrete Cosine Transform

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Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.


Circuits and Systems for Video Technology, IEEE Transactions on

Video A/D and D/A, display technology, image analysis and processing, video signal characterization and representation, video compression techniques and signal processing, multidimensional filters and transforms, analog video signal processing, neural networks for video applications, nonlinear video signal processing, video storage and retrieval, computer vision, packet video, high-speed real-time circuits, VLSI architecture and implementation for video technology, multiprocessor systems--hardware and software-- ...


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computers, IEEE Transactions on

Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...


Consumer Electronics, IEEE Transactions on

The design and manufacture of consumer electronics products, components, and related activities, particularly those used for entertainment, leisure, and educational purposes


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Most published Xplore authors for Discrete Cosine Transform

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Xplore Articles related to Discrete Cosine Transform

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Frequency cosine transform: A bridge between gradient based frequency transform and discrete cosine transform

2008 International Conference on Neural Networks and Signal Processing, 2008

Discrete cosine transform(DCT) is one of the most powerful tools in image processing. In this paper, we show that each basis of the two dimensional discrete cosine transform (2D-DCT) is an ldquoeigenvectorrdquo of the frequency matrix which is used to obtain basis images of a two dimensional frequency transform (2D-FRT). We also connect the FRT and cosine transform in 1D ...


IEEE Standard Specifications for the Implementations of 8X8 Inverse Discrete Cosine Transform

IEEE Std 1180-1990, 1991

This standard specifies the numerical characteristics of the 8*8 inverse discrete cosine transform (IDCT) for use in visual telephony and similar applications where the 8*8 IDCT results are used in a reconstruction loop. The specifications ensure the compatibility between different implementations of the IDCT.<<ETX>>


Fast Algorithm for Arbitrary Length Discrete Cosine Transform

2009 Fifth International Conference on Natural Computation, 2009

Based on discrete Hartley transform algorithm, the proposed fast algorithm is implemented by the parallel Hopfield neural network which can shorten the computation length of discrete cosine transform to achieve high computation speed. The computation complexity of the proposed method is reduced comparing with the others. According to the proposed algorithm which can implement the arbitrary length of discrete cosine ...


A fast modified signed Discrete Cosine Transform for image compression

2014 9th International Conference on Computer Engineering & Systems (ICCES), 2014

The Discrete Cosine Transform (DCT) is widely used in image compression for its high power compaction property. The Signed DCT (SDCT) and its modifications approximate the DCT and proceed faster. This paper introduces an efficient and low complexity 8 point transform. The proposed algorithm is derived by applying the signum function operator to an existing SDCT modification transform with good ...


Generalized Discrete Cosine Transform

2009 Pacific-Asia Conference on Circuits, Communications and Systems, 2009

The discrete cosine transform (DCT), introduced by Ahmed, Natarajan and Rao, has been used in many applications of digital signal processing, data compression and information hiding. There are four types of the discrete cosine transform. In simulating the discrete cosine transform, we propose a generalized discrete cosine transform with three parameters, and prove its orthogonality for some new cases. Finally, ...


More Xplore Articles

Educational Resources on Discrete Cosine Transform

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IEEE-USA E-Books

  • Frequency cosine transform: A bridge between gradient based frequency transform and discrete cosine transform

    Discrete cosine transform(DCT) is one of the most powerful tools in image processing. In this paper, we show that each basis of the two dimensional discrete cosine transform (2D-DCT) is an ldquoeigenvectorrdquo of the frequency matrix which is used to obtain basis images of a two dimensional frequency transform (2D-FRT). We also connect the FRT and cosine transform in 1D continuous model. Then, the frequency cosine transform (FCT), is proposed based on the FRT and the DCT. The partial frequency cosine transform (PFCT) is given and discussed in details. It is shown that the FCT can be regarded as a special case of FRT or DCT and it is as sophisticated as the FRT and as fast as the DCT.

  • IEEE Standard Specifications for the Implementations of 8X8 Inverse Discrete Cosine Transform

    This standard specifies the numerical characteristics of the 8*8 inverse discrete cosine transform (IDCT) for use in visual telephony and similar applications where the 8*8 IDCT results are used in a reconstruction loop. The specifications ensure the compatibility between different implementations of the IDCT.<<ETX>>

  • Fast Algorithm for Arbitrary Length Discrete Cosine Transform

    Based on discrete Hartley transform algorithm, the proposed fast algorithm is implemented by the parallel Hopfield neural network which can shorten the computation length of discrete cosine transform to achieve high computation speed. The computation complexity of the proposed method is reduced comparing with the others. According to the proposed algorithm which can implement the arbitrary length of discrete cosine transform, the N-point discrete cosine transform requires 2(N-1) real multiplications and 3N-2 real additions. Thus, the algorithm has a better application prospect in signal processing.

  • A fast modified signed Discrete Cosine Transform for image compression

    The Discrete Cosine Transform (DCT) is widely used in image compression for its high power compaction property. The Signed DCT (SDCT) and its modifications approximate the DCT and proceed faster. This paper introduces an efficient and low complexity 8 point transform. The proposed algorithm is derived by applying the signum function operator to an existing SDCT modification transform with good power compaction capabilities. Consequently, the elements of the proposed transform are only zeroes and ones. No multiplications or shift operations are required. The introduced transform keeps the high power compaction capabilities of its originating transform and, in the same time, provides a saving in computational complexity. A flow diagram is provided for the fast implementation of the transform. Only 17 additions are required for both forward and backward transformations. Simulation experiments are provided to justify the efficiency and improved performance of the proposed transform in image compression compared to other transforms.

  • Generalized Discrete Cosine Transform

    The discrete cosine transform (DCT), introduced by Ahmed, Natarajan and Rao, has been used in many applications of digital signal processing, data compression and information hiding. There are four types of the discrete cosine transform. In simulating the discrete cosine transform, we propose a generalized discrete cosine transform with three parameters, and prove its orthogonality for some new cases. Finally, a new type of discrete cosine transform is proposed and its orthogonality is proved.

  • Reduction of discrete cosine transform/ quantisation/inverse quantisation/inverse discrete cosine transform computational complexity in H.264 video encoding by using an efficient prediction algorithm

    This study develops a novel prediction algorithm to effectively save the computational complexity of discrete cosine transform (DCT), quantisation (Q), inverse Q (IQ), and inverse DCT (IDCT) in video encoding for H.264 applications. Based on the DC value of the DCT coefficients that is equal to the sum of residual data in the 4times4 sub-macroblock (sub-MB), a mathematical model is built to develop a prediction algorithm for reducing the computations in the DCT/Q/IQ/IDCT process. Experimental results and comparisons demonstrate that the proposed prediction algorithm significantly reduces the encoding time while incurring little additional overhead, and lowers the bit rate with little peak signal-to-noise ratio degradation.

  • Discrete Cosine Transform

    A discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed. It is shown that the discrete cosine transform can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering. Its performance is compared with that of a class of orthogonal transforms and is found to compare closely to that of the Karhunen-Lo&#232;ve transform, which is known to be optimal. The performances of the Karhunen-Lo&#232;ve and discrete cosine transforms are also found to compare closely with respect to the rate- distortion criterion.

  • Study on igneous rocks identification using full gradient of potential field based on discrete cosine transform

    Edge detection and enhancement techniques are usually used in identifying the boundary of geologic bodies using potential field data. In this paper, we present an igneous rocks identification method using full gradient of potential field based on discrete cosine transform. Rocks physical properties for igneous rocks usually have high-density and high magnetic susceptibility, with strong gravity or magnetic anomaly. So it's available to identify the boundaries and distribution of igneous rocks using full gradient of gravity and magnetic anomalies method. Discrete cosine transform was used in computing full gradient of potential field to improve the computational speed and accuracy. The modeling test proves good results based on the method we have discussed. Using this method, we identified igneous rocks distribution of northwestern South China Sea and its adjacent regions.

  • Text detection algorithm on real scenes images and videos on the base of discrete cosine transform and convolutional neural network

    In this work we present algorithms which are applied in such task as text recognition on images and video. Proposed algorithm is based on the combination of discrete cosine transform and convolutional neural networks. Description of the applying features of discrete cosine transform for text detection is provided. We list the main advantages and disadvantages of CNN and DCT combination. Also in this article we are going to consider methods of convolution neural networks for the task of text recognition.

  • High-Precision and Fixed-Point Discrete Cosine Transform without Multiplications

    Discrete cosine transform (DCT) is an important tool in digital signal processing. In this paper, based on our previous work of performing DCT via linear sums of discrete moments, we have made development to eliminate multiplications in discrete cosine transforms by performing appropriate bit operations and shift in binary system, which can be implemented by integer additions of fixed points. An efficient and regular systolic array is designed to implement it, and the complexity analysis is also given. Different to other fast cosine transforms, our algorithm can deal with arbitrary length signals and get high precision. The approach is also applicable to multi-dimensional DCT and DCT inverses.



Standards related to Discrete Cosine Transform

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IEEE Standard Specifications for the Implementations of 8x8 Inverse Discrete Cosine Transform

A standard is described to specify the numerical characteristics of the 8x8 Inverse Discrete Cosine Transform (IDCT) for use in visual telephony and similar applications where the 8x8 IDCT results are used in a reconstruction loop. The specifications ensure the compatibility between different implementations of the IDCT.



Jobs related to Discrete Cosine Transform

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